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Enabling Stateful TCP Performance Profiling with key Event Capturing

IEEE Transactions on Network and Service Management 2025年

作者： Geng, Ruopeng Lu, Jianyuan Fang, Chongrong Zhang, Shaokai Zhao, Jiangu Zong, Zhigang Lyu, Biao Zhu, Shunmin Cheng, Peng Chen, Jiming Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Alibaba Group Hangzhou310052 China Ministry of Education of China Key Laboratory of System Control and Information Processing China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China Zhejiang University College of Control Science and Engineering Hangzhou310027 China

TCP ensures reliable transmission through its stateful implementation and remains crucial today. TCP performance profiling is essential for tasks like diagnosing network performance problems, optimizing transmission performance, and developing new TCP variants, etc. Existing profiling methods lack enough attention to TCP state transition to provide detailed insights on TCP performance. Thus, we build TcpSight, a tool focusing on TCP state transition throughout connection lifetimes. TcpSight conducts stateful analysis by capturing key events using an efficient per-connection lock-free data management mechanism. Besides, TcpSight enhances profiling by integrating application layer information collected from the TCP stack. With the profiling results, users can identify the culprit of TCP performance degradation, and evaluate the performance of TCP algorithms. We design optional modules and filtering mechanisms to reduce TcpSights overhead. Our evaluation presents that TcpSight incurs an additional CPU consumption of about 16.6% (without filtering) and 10.6% (with filtering) when the server's load is 55.7%, and generates storage consumption about 1.88 KB per connection on average. We also give application cases of TcpSight and the deployment experiences in Alibaba Cloud. TcpSight helps in revealing meaningful findings and insights into exploiting TCP in the production deployment. © 2004-2012 IEEE.

关键词： information management

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Large-scale Multiobjective Optimization via Problem Decomposition and Reformulation

Large-scale Multiobjective Optimization via Problem Decompos...

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Congress on Evolutionary Computation

作者： Lianghao Li Cheng He Ran Cheng Linqiang Pan Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China

Large-scale multiobjective optimization problems (LSMOPs) are challenging for existing approaches due to the complexity of objective functions and the massive volume of decision space. Some large-scale multiobjective evolutionary algorithms (LSMOEAs) have recently been proposed, which have shown their effectiveness in solving some benchmarks and real-world applications. They merely focus on handling the massive volume of decision space and ignore the complexity of LSMOPs in terms of objective functions. The complexity issue is also important since the complexity grows along with the increment in the number of decision variables. Our previous study proposed a framework to accelerate evolutionary large-scale multiobjective optimization via problem reformulation for handling large-scale decision variables. Here, we investigate the effectiveness of LSMOF combined with decomposition-based MOEA (MOEA/D), aiming to handle the complexity of LSMOPs in both the decision and objective spaces. Specifically, MOEA/D is embedded in LSMOF via two different strategies, and the proposed algorithm is tested on various benchmark LSMOPs. Experimental results indicate the encouraging performance improvement benefited from the solution of the complexity issue in large-scale multiobjective optimization.

关键词： Sociology Evolutionary computation Benchmark testing Linear programming Complexity theory Statistics Optimization

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Error-free approximation of explicit linear MPC through lattice piecewise affine expression

arXiv

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arXiv 2021年

作者： Xu, Jun Lou, Yunjiang De Schutter, Bart Xiong, Zhenhua School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Delft Center for Systems and Control Delft University of Technology Netherlands State Key Laboratory of Mechanical Systems and Vibration Shanghai Jiao Tong University Shanghai China

In this paper, the disjunctive and conjunctive lattice piecewise affine (PWA) approximations of explicit linear model predictive control (MPC) are proposed. The training data are generated uniformly in the domain of interest, consisting of the state samples and corresponding affine control laws, based on which the lattice PWA approximations are constructed. Re-sampling of data is also proposed to guarantee that the lattice PWA approximations are identical to the explicit MPC control law in the unique order (UO) regions containing the sample points as interior points. Additionally, if all the distinct affine functions have been sampled, the disjunctive lattice PWA approximation constitutes a lower bound while the conjunctive lattice PWA approximation formulates an upper bound of the original optimal control law. The equivalence of the two lattice PWA approximations then guarantees that the approximations are error-free in the domain of interest, which is tested through a statistical guarantee. The complexity of the entire procedure is analyzed, which is polynomial with respect to the number of samples. The performance of the proposed approximation strategy is tested through two simulation examples, and the results show that with a moderate number of sample points, we can construct lattice PWA approximations that are equivalent to the optimal control law of the explicit linear MPC. © 2021, CC0.

关键词： Model predictive control

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SOS-based secure consensus control for stochastic nonlinear MASs against multiple DoS attacks

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Applied Mathematics and Computation 2025年 507卷

作者： Zhen Zhang Wei-Wei Che School of Automation Shandong Key Laboratory of Industrial Control Technology Qingdao University Qingdao 266071 Shandong China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 Liaoning China College of Information Science and Engineering Northeastern University Shenyang 110819 Liaoning China

This paper investigates the fully distributed fuzzy secure consensus control problem for stochastic nonlinear multi-agent systems (MASs). A polynomial fuzzy model is applied to reconstruct the system dynamics for a class of nonlinear MASs described by the I t o ˆ differential equation. The asynchronous denial-of-service (DoS) attack is considered that occurs independently across communication channels between the agents. Then, a novel fuzzy secure control protocol is developed to achieve the consensus task and resist the effect of the DoS attack. Meanwhile, the control protocol is fully distributed without relying on the global information of the Laplace matrix, and its adaptive parameter is membership-function-dependent, which is more flexible. Then, a non-parallel distributed compensation method is used to deal with the mismatch problem of the membership function between the fuzzy control protocol and the fuzzy system. In addition, several mean-square bounded convergence criteria in the form of the sum-of-squares for the secure tracking error are obtained by constructing the piecewise Lyapunov functions. Finally, the feasibility of the theoretical results is verified by the simulation example and the comparative analysis.

关键词： Denial-of-service attack Fully distributed fuzzy secure control Polynomial fuzzy model Stochastic nonlinear multi-agent system Sum-of-squares

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Finite control Set Model Predictive Position control of PMSM System

Finite Control Set Model Predictive Position Control of PMSM...

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第33届中国控制与决策会议

作者： Zhiqiang Wang Xiuyun Zhang Jie Bian School of Automobile and Transportation Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin University of Technology and Education Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Yunnan Industrial technician college

Servo drivers used for position control require higher dynamic performance in speed *** order to improve the dynamic response speed and position tracking accuracy of permanent magnet synchronous motor(PMSM) system,this paper proposes a control strategy for servo system based on finite control ***,the mathematical model of the PMSM system is established;then the reference voltage vector is predicted,and a speed expectation correction method is adopted to take into account system stability and fast followability;then the difference between the reference voltage vector and the candidate voltage vector is used as the improved cost function,and the selection of the candidate voltage vector and the optimization of the cost function are performed,to eliminate the complexity caused by the tuning of the weight *** that,considering the actual user needs,the current limit is integrated into the selection of the candidate voltage vector to achieve the current ***,the simulation research prove that the proposed control strategy can meet the requirements of dynamic response speed and position tracking accuracy.

关键词： Finite control set model predictive control(FCS-MPC) position control PMSM

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Predictive Speed Synchronous control of Dual Permanent Magnet Motor System Based on Quadratic Cost Function

Predictive Speed Synchronous Control of Dual Permanent Magne...

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第33届中国控制与决策会议

作者： Xiuyun Zhang Zhiqiang Wang Jie Bian School of Automation and Electrical Engineering Tianjin University of Technology and Education Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education School of Automobile and Transportation Tianjin University of Technology and Education Yunnan Industrial technician college

In order to solve the problem of reliance on manual experience and long time consuming for the weight coefficient setting in the predictive speed synchronous control of the dual permanent magnet motor system,this paper proposes a finite control set model predictive control strategy based on quadratic cost ***,based on the idea of unified modeling,the motion equation and electrical equation of the driving motor,the mathematical model of the two-level voltage source inverter are combined to establish a unified ***,the offline solution algorithm is used based on Lyapunov stability analysis to realize the self-tuning of the weight coefficient matrix,ensuring the convergence of each error term in the consecutive period;After that,the adjusted weight coefficient matrix is used for the online rolling optimization process of the predictive speed synchronous controller,and the cost function optimization is finally *** considering the actual user needs,the current limit is added to the ***,the simulation research prove that the proposed control strategy has fast dynamic response speed and synchronous tracking accuracy.

关键词： Finite control set model predictive control(FCS-MPC) synchronous control permanent magnet synchronous motor(PMSM)

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Non-cascaded Predictive Speed Synchronous control of Dual Permanent Magnet Motor System without Weight Coefficient Tuning

Non-cascaded Predictive Speed Synchronous Control of Dual Pe...

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第33届中国控制与决策会议

作者： Xiuyun Zhang Zhiqiang Wang Xiaolin Li Jie Bian School of Automation and Electrical Engineering Tianjin University of Technology and Education Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education School of Automobile and Transportation Tianjin University of Technology and Education Yunnan Industrial technician college

In order to improve the synchronous tracking accuracy of the dual permanent magnet motor system,this paper proposes a control strategy for dual permanent magnet motor system based on finite control ***,based on the idea of unified modeling,the motion equation and electrical equation of the driving motor,the mathematical model of the two-level voltage source inverter are combined to establish a unified ***,the reference voltage vectors with current and speed information are *** order to solve the problem of weight coefficient tuning in the traditional cost function,and simplify the complexity of the algorithm,the improved cost function is determined according to the ratio of contour error and tracking error,then the candidate voltage vectors are selected and the cost function is ***,the simulation research proves that the proposed control strategy can meet the dynamic and steady-state demand and synchronous control accuracy without weight coefficient tuning.

关键词： Finite control set model predictive control(FCS-MPC) synchronous control permanent magnet synchronous motor(PMSM)

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AIM 2024 Challenge on Video Saliency Prediction: Methods and Results

arXiv

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arXiv 2024年

作者： Zhan, Gen Yang, Li Tang, Yunlong Liao, Yiting Lin, Jiongzhi Huang, Baitao Moradi, Morteza Moradi, Mohammad Rundo, Francesco Spampinato, Concetto Borji, Ali Palazzo, Simone Zhu, Yuxin Sun, Yinan Duan, Huiyu Cao, Yuqin Jia, Ziheng Hu, Qiang Min, Xiongkuo Zhai, Guangtao Fang, Hao Cong, Runmin Lu, Xiankai Zhou, Xiaofei Zhang, Wei Zhao, Chunyu Mu, Wentao Deng, Tao Tavakoli, Hamed R. Moskalenko, Andrey Bryncev, Alexey Vatolin, Dmitry Timofte, Radu ByteDance China ByteDance United States University of Rochester United States College of Electronic and Information Engineering Shenzhen University China Shenzhen Key Laboratory of Digital Creative Technology China Guangdong Key Laboratory of Intelligent Information Processing China University of Catania Italy STMicrolectronics ADG Central R&D Italy Quintic AI San Francisco United States Shanghai Jiao Tong University China School of Control Science and Engineering Shandong University China School of Software Shandong University China School of Automation Hangzhou Dianzi University China School of Information Science and Technology Southwest Jiaotong University China Nokia Technologies Finland Lomonosov Moscow State University Russia AIRI Moscow Russia MSU Institute for Artificial Intelligence Russia University of Würzburg Germany

This paper reviews the Challenge on Video Saliency Prediction at AIM 2024. The goal of the participants was to develop a method for predicting accurate saliency maps for the provided set of video sequences. Saliency maps are widely exploited in various applications, including video compression, quality assessment, visual perception studies, the advertising industry, etc. For this competition, a previously unused large-scale audio-visual mouse saliency (AViMoS) dataset of 1500 videos with more than 70 observers per video was collected using crowdsourced mouse tracking. The dataset collection methodology has been validated using conventional eye-tracking data and has shown high consistency. Over 30 teams registered in the challenge, and there are 7 teams that submitted the results in the final phase. The final phase solutions were tested and ranked by commonly used quality metrics on a private test subset. The results of this evaluation and the descriptions of the solutions are presented in this report. All data, including the private test subset, is made publicly available on the challenge homepage - https://***/challenges/***. © 2024, CC BY.

关键词： Video analysis

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Optimizing the performance of the feedback controller for state-based switching bilinear systems

Optimizing the performance of the feedback controller for st...

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作者： Lin, Shu Li, Dewei Schutter, Bart School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China Delft Center for Systems and Control Delft University of Technology Delft Netherlands

This article is concerned with the design and performance optimization of feedback controllers for state-based switching bilinear systems (SBLSs), where subsystems take the form of bilinear systems in different state space polyhedra. First, by further dividing the subregions into smaller regions and designing region-dependent feedback controllers in the resulting regions, the SBLSs can be transformed into corresponding switching linear systems (SLSs). Then, for these SLSs, by imposing contractility conditions on the Lyapunov functions, an upper bound on the infinite horizon quadratic cost can be obtained. Optimizing this upper bound yields the controller design. The optimization problem is formulated as a linear matrix inequalities optimization problem, which can be solved efficiently. Finally, the stability of the close-loop system under the proposed controller is established step by step through a decreasing overall Lyapunov function. © 2020 John Wiley & Sons, Ltd.

关键词： Lyapunov functions

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Switched High-Gain Based Interval Observer Design for Harmonic Oscillator System

Switched High-Gain Based Interval Observer Design for Harmon...

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Chinese control Conference (CCC)

作者： Tianhang Ming Xiaoling Wang Bo Liu Housheng Su College of Automation & AI Nanjing University of Posts and Telecommunications Nanjing P. R. China Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing China College of Information Engineering Minzu University of China Beijing P. R. China Key Laboratory of Image Processing and Intelligence Control of Ministry of Education Huazhong University of Science and Technology Wuhan P. R. China

In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturbance and measurement noise, a high-gain interval observer is firstly defined and constructed for the harmonic oscillator system to realize the interval estimation on the state and the robust control of the system. Then, a switched high-gain interval observer is proposed to reduce the influence of the measurement noise for a tighter interval width on the state estimation. Finally, some numerical simulations are given to verify the theoretical results.

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